Corpus callosum area in patients with bipolar disorder with and without psychotic features: an international multicentre study
Bibliographic record
Abstract
BACKGROUND: Previous studies have reported MRI abnormalities of the corpus callosum (CC) in patients with bipolar disorder (BD), although only a few studies have directly compared callosal areas in psychotic versus nonpsychotic patients with this disorder. We sought to compare regional callosal areas in a large international multicentre sample of patients with BD and healthy controls. METHODS: We analyzed anatomic T1 MRI data of patients with BD-I and healthy controls recruited from 4 sites (France, Germany, Ireland and the United States). We obtained the mid-sagittal areas of 7 CC subregions using an automatic CC delineation. Differences in regional callosal areas between patients and controls were compared using linear mixed models (adjusting for age, sex, handedness, brain volume, history of alcohol abuse/dependence, lithium or antipsychotic medication status, symptomatic status and site) and multiple comparisons correction. We also compared regional areas of the CC between patients with BD with and without a history of psychotic features. RESULTS: We included 172 patients and 146 controls in our study. Patients with BD had smaller adjusted mid-sagittal CC areas than controls along the posterior body, the isthmus and the splenium of the CC. Patients with a positive history of psychotic features had greater adjusted area of the rostral CC region than those without a history of psychotic features. LIMITATIONS: We found small to medium effect sizes, and there was no calibration technique among the sites. CONCLUSION: Our results suggest that BD with psychosis is associated with a different pattern of interhemispheric connectivity than BD without psychosis and could be considered a relevant neuroimaging subtype of BD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".